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Article

Analysis of IEC 61850-9-2LE Measured Values Using a Neural Network

Brno University of Technology, Technicka 12, 616 00 Brno, Czech Republic
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Energies 2019, 12(9), 1618; https://doi.org/10.3390/en12091618
Received: 27 February 2019 / Revised: 23 April 2019 / Accepted: 26 April 2019 / Published: 28 April 2019
(This article belongs to the Special Issue Data Analytics in Energy Systems)
Process bus communication has an important role to digitalize substations. The IEC 61850-9-2 standard specifies the requirements to transmit digital data over Ethernet networks. The paper analyses the impact of IEC 61850-9-2LE on physical protections with (analog-digital) input data of voltage and current. With the increased interaction between physical devices and communication components, the test proposes a communication analysis for a substation with the conventional method (analog input) and digital method based on the IEC 61850 standard. The use of IEC 61850 as the basis for smart grids includes the use of merging units (MUs) and deployment of relays based on microprocessors. The paper analyses the merging unit’s functions for relays using IEC 61850-9-2LE. The proposed method defines the sampled measured values source and analysis of the traffic. By using neural net pattern recognition that solves the pattern recognition problem, a relation between the inputs (number of samples/ms—interval time between the packets) and the source of the data is found. The benefit of this approach is to reduce the time to test the merging unit by getting the feedback from the merging unit and using the neural network to get the data structure of the publisher IED. Tests examine the GOOSE message and performance using the IEC standard based on a network traffic perspective. View Full-Text
Keywords: IEC61850; SMV; sampled value; GOOSE; Ethernet; SVScout; delay time; IED; time synchronization; machine learning; ROCs IEC61850; SMV; sampled value; GOOSE; Ethernet; SVScout; delay time; IED; time synchronization; machine learning; ROCs
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MDPI and ACS Style

Wannous, K.; Toman, P.; Jurák, V.; Wasserbauer, V. Analysis of IEC 61850-9-2LE Measured Values Using a Neural Network. Energies 2019, 12, 1618. https://doi.org/10.3390/en12091618

AMA Style

Wannous K, Toman P, Jurák V, Wasserbauer V. Analysis of IEC 61850-9-2LE Measured Values Using a Neural Network. Energies. 2019; 12(9):1618. https://doi.org/10.3390/en12091618

Chicago/Turabian Style

Wannous, Kinan, Petr Toman, Viktor Jurák, and Vojtěch Wasserbauer. 2019. "Analysis of IEC 61850-9-2LE Measured Values Using a Neural Network" Energies 12, no. 9: 1618. https://doi.org/10.3390/en12091618

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